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43 results on '"Chen, Tingjie"'

8. A Simple and Effective Physical Ball‐Milling Strategy to Prepare Super‐Tough and Stretchable PVA@MXene@PPy Hydrogel for Flexible Capacitive Electronics

Author

Qin, Zipeng, primary, Zhao, Gang, additional, Zhang, Yaoyang, additional, Gu, Zhiheng, additional, Tang, Yuhan, additional, Aladejana, John Tosin, additional, Ren, Junna, additional, Jiang, Yunhong, additional, Guo, Zhanhu, additional, Peng, Xiangfang, additional, Zhang, Xuehua, additional, Xu, Ben Bin, additional, and Chen, Tingjie, additional

Published
2023
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9. `Pandem-icons' — exploring the characteristics of highly visible scientists during the Covid-19 pandemic

Author

Joubert, Marina, primary, Guenther, Lars, primary, Metcalfe, Jenni, primary, Riedlinger, Michelle, primary, Chakraborty, Anwesha, primary, Gascoigne, Toss, primary, Schiele, Bernard, primary, Baram-Tsabari, Ayelet, primary, Malkov, Dmitry, primary, Fattorini, Eliana, primary, Revuelta, Gema, primary, Barata, Germana, primary, Riise, Jan, primary, Schröder, Justin T., primary, Horst, Maja, primary, Kaseje, Margaret, primary, Kirsten, Marnell, primary, Bauer, Martin W., primary, Bucchi, Massimiano, primary, Flores, Natália, primary, Wolfson, Orli, primary, and Chen, Tingjie, primary

Published
2023
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14. Solar-Assisted High-Efficient Cleanup of Viscous Crude Oil Spill Using an Ink-Modified Plant Fiber Sponge

Author

Liu, Zhiyong, primary, Chen, Mengyao, additional, Lin, Che, additional, Li, Fuying, additional, Aladejana, John Tosin, additional, Hong, Jiahui, additional, Zhao, Gang, additional, Qin, Zipeng, additional, Zhu, Xiaowang, additional, Zhang, Weijie, additional, Chen, Dinggui, additional, Peng, Xiangfang, additional, and Chen, Tingjie, additional

Published
2022
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24. Effect of Boron-Zinc-Aluminum-Silicium Compounds on the Fire Performance of Ultra-Low Density Fiberboards

Author

Wu, Zhenzeng, Chen, Tingjie, Niu, Min, Cai, Lili, Xie, Yongqun, and Wang, Alice

Subjects
Optimization, 0106 biological sciences, Environmental Engineering, Materials science, lcsh:Biotechnology, chemistry.chemical_element, Bioengineering, Sodium silicate, 02 engineering and technology, Zinc, Fire performance, 01 natural sciences, Limiting oxygen index, chemistry.chemical_compound, lcsh:TP248.13-248.65, 010608 biotechnology, Cone calorimeter, Sulfate, Composite material, Boron, Waste Management and Disposal, Annan maskinteknik, Borax, B-Zn-Si-Al compounds, 021001 nanoscience & nanotechnology, chemistry, Ultra-low density, Other Mechanical Engineering, 0210 nano-technology, Nuclear chemistry, Fire retardant
Abstract

B-Zn-Si-Al compounds are modified Si-Al compounds made of sodium silicate, zinc sulfate, borax, and aluminum sulfate. They act as a fire retardant during the preparation of ultra-low density fiberboards (ULDFs). An orthogonal experiment was used to optimize the contents of the four compounds according to the limiting oxygen index. Fourier transform infrared spectroscopy was employed to preliminarily analyze the chemical structure of the compounds. Additionally, a cone calorimeter was used to assess the fire performance of the ULDFs. The results suggested that the optimized solution was made of 27.0 mL of sodium silicate solution, 27.0 mL of aluminum sulfate solution, 3.0 g of zinc sulfate, and 6.5 g of borax, resulting in an oxygen index of 29.5%. The bond Al-O-B was detected at 1397 and 796 cm-1. The Si-O-Zn bonds were detected at 867 cm-1. The heat release rate, total heat release, and total smoke release decreased and the mass residual ratio increased in the sample using the optimal conditions from the orthogonal array design. It was concluded that B-Zn- Si-Al compounds effectively protect fibers from fire. Validerad; 2016; Nivå 2; 20160331 (aliwan)

Published
2016

43. Model Update Strategies about Object Tracking: A State of the Art Review.

Author

Wang, Deyu, Fang, Weidong, Chen, Wei, Sun, Tongfeng, and Chen, Tingjie

Subjects
OBJECT tracking (Computer vision), COMPUTER vision, ARTIFICIAL satellite tracking
Abstract

Object tracking has always been an interesting and essential research topic in the domain of computer vision, of which the model update mechanism is an essential work, therefore the robustness of it has become a crucial factor influencing the quality of tracking of a sequence. This review analyses on recent tracking model update strategies, where target model update occasion is first discussed, then we give a detailed discussion on update strategies of the target model based on the mainstream tracking frameworks, and the background update frameworks are discussed afterwards. The experimental performances of the trackers in recent researches acting on specific sequences are listed in this review, where the superiority and some failure cases on each of them are discussed, and conclusions based on those performances are then drawn. It is a crucial point that design of a proper background model as well as its update strategy ought to be put into consideration. A cascade update of the template corresponding to each deep network layer based on the contributions of them to the target recognition can also help with more accurate target location, where target saliency information can be utilized as a tool for state estimation. [ABSTRACT FROM AUTHOR]

Published
2019
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